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Grounded Visual Pattern Analysis: Photographs in Organizational Field Studies

Shortt, Harriet; Warren, Samantha

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Harriet Shortt
Associate Professor in Organisation Studies

Samantha Warren


© The Author(s) 2017. Visual methodologies for researching organizational life have grown in popularity over the past decade, with conceptual and methodological foundations now well documented. However, analytical critique has not kept pace, and so in this article we offer grounded visual pattern analysis (GVPA) as a rigorous means of analysis that mines the discursive meanings of individual photographs and the visual patterns apparent across multiple still images. We illustrate GVPA’s value through an ethnographic field study investigating the relationship between workplace environments and identity formation among hair salon workers in the United Kingdom. Specifically, we explain how to combine the strengths of both “dialogical” and “archaeological” approaches to visual research, which have hitherto been seen as distinct endeavors. We argue this is particularly valuable in field studies addressing material turns in organization studies, such as studies of space, strategy-as-practice, embodied cognition, and servicescape aesthetics. The article concludes by putting forward a series of potential directions for the future of visual organizational research based on the bridging of Meyer et al.’s five different methodological approaches.


Shortt, H., & Warren, S. (2019). Grounded Visual Pattern Analysis: Photographs in Organizational Field Studies. Organizational Research Methods, 22(2), 539-563.

Journal Article Type Article
Acceptance Date Dec 11, 2017
Online Publication Date Dec 11, 2017
Publication Date Apr 1, 2019
Deposit Date Mar 5, 2018
Publicly Available Date Mar 9, 2018
Journal Organizational Research Methods
Print ISSN 1094-4281
Electronic ISSN 1552-7425
Publisher SAGE Publications
Peer Reviewed Peer Reviewed
Volume 22
Issue 2
Pages 539-563
Keywords ethnography, field research methods, photography, qualitative research, visual analysis, visual methods
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Publisher URL
Additional Information Additional Information : © 2019. Reprinted by permission of SAGE Publications


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